An interdisciplinary research effort between computer scientists and experts in neuromuscular disease is proposed. The primary goal of this project is to develop automated techniques to supplement or replace the manual histomorphometric methods that are currently used in the analysis of muscle and nerve biopsies. The automated techniques should prove to be more reliable and useful than their manual counterparts which are comparatively tedious, time consuming, and often error prone. This is potentially a very valuable project because neuromuscular diseases are among the commonest causes of chronic disability in man, and histomorphometric analysis of biopsy sections of nerve and muscle tissue is an important technique used in research aimed at understanding these diseases, and in the diagnosis and clinical mangement of patients. Specifically, it is proposed: (1) to develop and evaluate computer-assisted image analysis techniques for counting and characterizing human nerve and muscle fibers as seen in histologic sections; and (2) to demonstrate the usefulness of these techniques in an actual research application. The long range goals are; first, to make quantitative morphometric analysis of nerve and muscle fibers more accurate, less tedious and hence more available for research and clinical applications; and second, to explore the possibility that automated analysis will make feasible certain histomorphometric measurements in nerve and muscle tissue that are currently impossible or impractical by manual means.